California Hybrid, Efficient and Advanced Truck Research Center California Truck Inventory and Impact Study November 30, 2011 Geoff Jennings Tom Brotherton For more information visit: CalHEAT www.calheat.org California Energy Commission www.energy.ca.gov CALSTART www.calstart.org Purpose and Summary This paper serves as a summary of the methodology and findings of the California Truck Inventory Study undertaken by CalHEAT. The goal of the study is to better understand the various types of trucks used in California, their relative populations, and how they are used. As the State looks to technologies with the ability to reduce petroleum consumption, it is imperative to understand that technologies will have widely varying impacts depending on the truck’s characteristics and how it used. For example, a box truck used for heavy urban cycles may benefit greatly from hybridization or electrification, whereas a truck used to drive between Los Angeles and San Francisco may benefit more from aerodynamic improvements and lightweighting. The ultimate goal of CalHEAT is to help the State develop a plan to meet 2020 goals in petroleum reduction, carbon reduction and air quality standards, as well as set up a framework and timeline for longer-term goals for carbon reduction. As CalHEAT prepares the transformation roadmap, which will coordinate the development of an overall research and market transformation plan and as CalHEAT facilitates that plan’s implementation, it is important, first and foremost, that the different truck use types are clearly understood. Then, it is possible to move on to which of the various technologies might best address each type. Characterization of Vehicle Populations Trucks in California A solid foundation for building the roadmap requires a clear understanding of the California fleet. It is necessary to know the number of trucks in different size categories, and how they are used. Data from a variety of sources has been collected and analyzed. The primary resources are:  database maintained by R. L. Polk & Co, which lists every vehicle registered in the state, along with information about each vehicle;1  2002 Vehicle Inventory and Use Survey VIUS study from the U.S. Census;2  May 2008 edition of Climate Registry’s General Reporting Protocol (GRP);3 and  2008 California Air Resource Board Truck and Bus study.4,5 https://www.polk.com/knowledge/reports- CalHEAT worked with Polk to create a custom dataset from their database, which covers registered vehicles in CA 2 http://www.census.gov/svsd/www/vius/2002.html 3 http://www.theclimateregistry.org/downloads/GRP.pdf 4 http://www.arb.ca.gov/regact/2008/truckbus08/truckbus08.htm 1 2 CalHEAT Truck Model Analysis The analysis included nearly 1.5 million trucks and buses, ranging in size from Class 2B to Class 8. This number is based upon California registration figures, for commercial trucks in the weight category 2B and above, via the Polk database. It does not represent out of state trucks operating in California, but does include trucks registered here that operate out of state. Future analysis will need to compensate for these factors, likely building on the work done at UC Davis.6 Some assumptions were made, particularly in class 2B, to attempt to separate commercial vehicles from non-commercial vehicles. The trucks in class 2B, registered to “Individuals,” were eliminated under the assumption that most, if not all, were non-commercial vehicles. Table 1: Vehicle Classes 5 6 http://www.arb.ca.gov/regact/2008/truckbus08/emissinv.xls http://pubs.its.ucdavis.edu/publication_detail.php?id=1176 3 Truck Fuel Use As Figure 1 shows, the medium- and heavy-duty vehicle market uses more diesel than gasoline. This is not because there are more diesel trucks; in fact, there are more gasoline vehicles by total number. However, because the heaviest trucks use the most fuel, and are nearly 100% diesel, total diesel fuel use is higher. As one moves up the weight classes, the percentage of vehicles burning gasoline goes from being overwhelmingly gas on the light-duty end, to nearly 100% diesel in the Class 8 segment. The CEC reports there were about 15 billion gallons of gasoline used in CA in 2008 (mostly in light-duty passenger cars and light trucks), a number expected to decline by 3-6% annually through 2020. According to the same report, diesel fuel use, in contrast, is estimated at 3.6 billion gallons, and expected to increase by 1.5% annually in the same time period.7 Commercial trucks and buses account for approximately 30 percent (5.8 billion gallons) of the 18.6 billion gallons of petroleum fuel used by vehicles in the State.8 Figure 1: Truck Fuel Use: Percentage by Fuel Type Truck Fuel Use Diesel Gasoline Natural Gas 1% Propane, Electric and others <1% 38% 60% http://ntl.bts.gov/lib/32000/32700/32779/DOT_Climate_Change_Report_-_April_2010__Volume_1_and_2.pdf 8California DOT, “2008 California Motor Vehicle Stock, Travel and Fuel Forecast”, 2008 7 4 Truck Population by Weight Class Of the nearly 1.5 million trucks in California, Class 2b, Class 3 and Class 8 have around 300,000 each. Class 5 has the fewest vehicles, with about 75,000. Figure 2: Truck Population by Weight Class CalHEAT’s Six Truck Categories For the purposes of CalHEAT’s roadmap data, it was apparent that the weight classes were not sufficient to evaluate the impact of technology. With significant input from the CalHEAT Technology Advisory Group and the CalHEAT Advisory Council, six categories of trucks were developed. The intent behind the formation of these categories was to lump together trucks that are used in similar ways, such that it could be assumed that there may be similar impacts from technologies. A Class 4 truck in heavy urban use might see a similar percent improvement from hybridization that a Class 6 truck in a similar use would. These trucks would be more similar in how they are affected by a given technology than a Class 4 Truck primarily used for long distance freeway driving. The six truck categories, with primary defining guidelines, are as follows. (Pictures are merely representative and not meant to be inclusive.) 5  Class 7-8 Over the Road (OTR) o Younger trucks o High annual VMT o Mostly higher average speed, highway driving  Class 7-8 Short Haul/Regional o Between cities o Drayage o Day cabs o Includes second use trucks and trucks with smaller engines  Class 3-8 Urban o Cargo, freight, delivery collection o Lower VMT o Lower average speed o Lots of stop start  Class 3-8 Rural/Intracity o Cargo, freight, delivery collection o Higher VMT o Higher average speed o Combination of urban and highway traffic  Class 3-8 Work Site Support o Utility trucks, construction, etc. o Lots of idle time o Lots of PTO use 6  Class 2b -3 Vans and Pickups To better and more accurately characterize the fleet, vocational attributes were tracked in the data. By tracking vocation and calculating the impact of trucks in different vocations, weight classes and vehicle types, it is possible to accurately characterize the California fleet. By further identifying which segments of the population have the biggest impacts, technologies, market tools and opportunities can be identified for those populations. With 1.5 million trucks in the database, no sorting process was going to be perfect in assigning trucks to the six categories. CalHEAT’s process built a large matrix of attributes, with logic steps applied in a certain order, to assign each of the trucks to the category to which they were most likely to belong. The characteristics used for sorting included:  Vocation o The registered business type of the owner sometimes gives clues as to how a truck might be used. Utility trucks would have a higher percentage of work site support. Agriculture registered Class 8 trucks are more likely used for rural and intercity delivery routes.  Registered Truck Type and Size o From the original data set, certain attributes are known, e.g. box truck vs. stake bed vs. tractor vs. bus.  Model Assessment o First, sorting the 1.5 million trucks by GVW, manufacture and model name and then filtering trucks with less than four examples in the fleet, left about 2400 model names. Each was looked up, researched and assigned to 24 truck types, e.g. work truck, fire truck, tractor or sleeper cab. Some model names applied only to one certain type of truck, others referred to a cab and chassis that might have many different final uses, so there was some degree of variability in the confidence of the assignment.  Engine Size  Age 7 No single variable was used for sorting; each truck was evaluated on multiple variables before being assigned to one of the six truck categories. Some percentage of trucks, mostly older trucks, had insufficient data to assign to any category. Once the trucks were sorted, with this and other data, vehicle groups were assigned average weights and average fuel consumption, average vehicle miles travelled, and estimates of carbon emissions (per mile/hour) based on their class, body type and engine size. Calculated aggregate results were compared with other published studies, and the results were consistent. This study calculated a 2010 estimate for million metric tons of C02 equivalent of 36.97 MMTCO2e, which is 106 percent of the 2008 ARB estimate of 34.79 MMTCO2e. This difference aligns with expected growth in fuel use, and also indicates that CalHEAT’s calculations are in line with anticipated results. Similarly, the calculated annual VMT found in this study was compared with published numbers from the Air Resource Board for 2008, and found to be within a few percentage points of 2008 numbers. Figure 3 provides a look at the relative size of the six categories. Class 2b/3 Vans/Pickups make up about one-third of the total. Figure 3: Population by Truck Category Population by Truck Category 600000 500000 400000 300000 200000 100000 0 Tractors - OTR Class 3 - 8 Class 3 - 8 Class 2b/3 Tractors Class 3 - 8 Work Trucks - Work Trucks - vans/pickups Short Haul/ Work Trucks Rural/ Urban Regional Work Site Intracity Support 8 Unknown Figure 4 below is a visualization of one way to look at this data. Each bubble represents a vocation as tracked in the Polk Database – relative GHG emissions (as C02e) as the area of the circle, with vehicle miles travelled (VMT) as the y-axis and population as the x-axis. Here, for example, you can see that although the Category Class 2b/3 contains by far the largest number of trucks, OTR Tractors have much higher average VMT are responsible for much more CO2. Figure 4: Truck CO2, Average VMT and Population by Truck Category Current analysis indicates that although the Class 8 OTR category is clearly a large and important target, nearly every category plays a very significant role. As technologies are evaluated, it can be shown that a 20% gain in the Class 3-8 Work Trucks, applied across three segments, could impact the state population in similar amounts to a 10% reduction in OTR tractors. The data set is structured in such a way as to allow sorting in many ways, among others by geography, vocation, vehicle class and particular pollutants. Additionally, this study gives us 9 the ability to look at where trucks are registered, which may assist in evaluating specific programs for certain regions or air districts. Figures 5, 6 and 7 provide just a few of the many ways these categories can be sorted and analyzed. Following these figures, Table 2 displays some of the database codes and their sources. Figure 5: Percent Fuel Use by Type and Truck Category 10 Figure 6: Truck Age Distribution by Decade Figure 7: Truck Categories by Gross Vehicle Weight 11 Table 2: Database Codes and Sources Database Code MSA Meaning Location Source Data Reg Zip Bas First three digits of the zip code Data VGVW Weight Classification Data YM Year of Manufacture Data Cab Info regarding the cab type of the vehicle -- limited value Data VType Info regarding the vehicle type -- sometimes useful, but some categories are very broad Data Make Manufacture Data Veh Model Model Name Data Veh Series Model Series Data E Mfr Engine Manufacture Data Engine Model Engine Model Data Liters Engine Size Data Cyl Number of Cylinders Data CID Cubic Inch Displacement Data Fuel Fuel Type Data Reg CT Registered Carrier type (private, individual, govt or for lease) Data Reg Voc Registered "Vocation" -- the tax code business type of the owner Data Std Cnt The number of vehicles in a registration row -- mostly 1 Data make/model concat Sorting Tool Assigned Code assigned Code assigned by CalHEAT Assigned Cat1-10 Sorting Tool Assigned Cat1-6 CalHEAT Categories by Number Assigned Names CalHEAT Categories by Name Assigned Adjustment Adjustment to estimates to account for usage type Assigned VMT (orig) VMT assigned based strictly on truck type Assigned VMT (revised) VMT assigned based on truck type and estimated usage Assigned Gal gasoline /yr Gal Gasoline used per year Calculated Gal Diesel /yr Gal Diesel used per year Calculated NG Natural Gas used per year Calculated Gal Natural Gas /yr Gal Equivalent NG per year Calculated Gal Other Fuel /yr Gal Equivalent other fuel Calculated g N2O /yr Grams N0X per year Calculated g CH4 /yr Grams CH4 per year Calculated kg CO2 /yr kg C02 per year Calculated Liter multiplier Sorting tool Calculated veh type id Sorting tool Calculated mileage id Sorting Tool Calculated Idling hours/yr Sorting Tool Calculated 12 Summary This detailed characterization will play an important role in the next phase of the roadmap development. Should it prove fruitful, it is possible to subdivide the above classifications to gain greater insight into the various sub-categories. That is, if a technology was known to apply to Box Trucks used in intercity routes, the number and impact of trucks in that category can be estimated. This detailed analysis is and will be a key component of estimating the impact of various technologies as the CalHEAT roadmap is developed. 13